Data Science with R Certification Training

Categories Analytics and Data Management Certification

No prior programming or data science experience is mandatory
Basic understanding of mathematics and statistics is helpful but not required
A laptop with internet access is required for hands-on labs
R and required tools will be guided during the training
Exam fee is included in the course fee
For rescheduling or cancellation, email Support@certificationguide.com
Course location, access links, and schedules will be shared after registration

This course is ideal for:
Aspiring Data Scientists
Data Analysts and Business Analysts
Software Developers and Engineers
IT Professionals looking to transition into Data Science
Fresh graduates and working professionals interested in analytics
Professionals working with data in finance, healthcare, marketing, and operations

4 days of intensive instructor-led training (In-person or Online)
Hands-on training with R and analytics tools
Courseware developed by industry experts
Real-world datasets, case studies, and projects
Exam tips and tricks for first-attempt success
Certification Guide Data Science with R Certificate
35 PDUs certificate upon course completion
Lifetime single-user access to downloadable course materials
100% Pass Guarantee and 100% Money-Back Guarantee

Description

The Data Science with R Certification Training by Certification Guide is a comprehensive, instructor-led program designed to help professionals master data analytics and data science using the R programming language. This course provides in-depth knowledge of R, its powerful libraries, and real-world applications for data manipulation, visualization, statistical analysis, and machine learning.

R is one of the most preferred languages for data science due to its robustness, flexibility, and extensive ecosystem of statistical and machine learning packages. This training equips learners with practical, job-ready skills through hands-on labs, real-life case studies, and project-based learning, enabling them to make data-driven decisions and build predictive models across industries.

After completing this Data Science with R course, you will be able to:
Understand the complete Data Science lifecycle and real-world business use cases
Work confidently with the R programming language and its core libraries
Perform data extraction, data wrangling, and exploratory data analysis (EDA)
Apply statistical inference techniques for data-driven decision-making
Visualize data effectively using R for insights and storytelling
Implement supervised and unsupervised machine learning algorithms
Build models using Decision Trees, Random Forest, Naive Bayes, SVM, and K-Means
Analyze and forecast data using Time Series models (ARIMA, ETS)
Understand the basics of Deep Learning and Neural Networks
Apply machine learning models to real-life datasets and business scenarios

Course Agenda

Introduction

Introduction to Course
Certification Guide, Instructor, Participant introduction and Set expectation by participant

Module 01 : Introduction to Data Science

What is Data Science?
What does Data Science involve?
The era of Data Science
Business Intelligence vs Data Science
The life cycle of Data Science
Tools of Data Science
Introduction to Big Data and Hadoop
Introduction to R
Introduction to Spark
Introduction to Machine Learning

Module 02 : Statistical Inference

Module 03 : Data Extraction, Wrangling, and Exploration

Module 04 : Introduction to Machine Learning

Module 05 : Classification Technique

Module 06 : Time Series

Module 07 : Deep Learning

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